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Spiking Neural Networks on High Performance Computer Clusters

机译:在高性能计算机群集上添加神经网络

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In this paper we examine the acceleration of two spiking neural network models on three clusters of multicore processors representing three categories of processors: x86, STI Cell, and NVIDIA GPGPUs. The x86 cluster utilized consists of 352 dualcore AMD Opterons, the Cell cluster consists of 320 Sony Playstation 3s, while the GPGPU cluster contains 32 NVIDIA Tesla S1070 systems. The results indicate that the GPGPU platform can dominate in performance compared to the Cell and x86 platforms examined. From a cost perspective, the GPGPU is more expensive in terms of neuron/s throughput. If the cost of GPGPUs go down in the future, this platform will become very cost effective for these models.
机译:在本文中,我们研究了代表三类处理器的多核处理器的三个群集上两个尖峰神经网络模型的加速:x86,STI Cell和NVIDIA GPGPU。使用的x86群集包含352个双核AMD皓龙,Cell群集包含320个Sony Playstation 3s,而GPGPU群集包含32个NVIDIA Tesla S1070系统。结果表明,与所检查的Cell和x86平台相比,GPGPU平台可以在性能上占主导地位。从成本角度来看,就神经元/ s吞吐量而言,GPGPU更为昂贵。如果将来GPGPU的成本下降,那么该平台对于这些型号将变得非常具有成本效益。

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